Organizations invest in technologies that provide customers with access to computing resources. Such services provide access to computing and/or storage resources (e.g., storage devices providing either a block-level device interface, or a web service interface) to customers or subscribers. Within multi-tier ecommerce systems, combinations of different types of resources may be allocated to customers and/or their applications, such as whole physical or virtual machines, CPUs, memory, network bandwidth, or I/O capacity. Block-level storage devices implemented at storage service may be made accessible, for example, from one or more physical or virtual machines implemented by another service.
Computer systems that provide services to customers may employ various techniques to protect the computer systems from a number of service requests that could potentially overload the computer systems. Furthermore, these computer systems may also employ various techniques to preserve customer data and customer experience during periods when the computer systems are overloaded or even experiencing failures. In general, a computer system is considered to be in an “overloaded” state if it is not able to provide the expected quality of service for at least some portion of customer requests it receives. Common solutions applied by overloaded computer systems include denying service to customers. In addition to this “overloaded” scenario, computer systems may also experience failure, including critical failure, power failure, or network failure.
To protect customer data against failures, customer data is often replicated across different computer systems. However, creating consistent replicas of customer data across a plurality of computer systems requires additional resources and requires consensus on customer data across the plurality of computer systems. Additionally, there is increase cost and time required to provision computer systems to maintain replicas of customer data. While such systems may maintain the integrity of customer data and mitigate the risk of loss, there may be a reduction in customer experience and delay in customers obtaining their data.